AI: Advancing Patient Access and Outcomes

Biocom’s 4th Annual Big Data Summit, held October 29, 2019 in La Jolla, CA, brought together thought leaders in artificial intelligence (AI), computational drug discovery, and blockchain technology. Throughout the day a recurring theme emerged: machine learning improves the affordability, speed, quality and utility of complex applications. Technology advancements over the last 5 years have opened up the possibilities for the life science industry, and access to real data has revolutionized how we think about achievable solutions to therapies and decision support diagnosis tools. 

AI is not about outperforming the physician – but rather automating processes, and expanding the potential for larger, more complex applications. The discussions should not revolve around replacing humans/doctors, but rather expanding access and continuing to put the needs of the patient first. For instance, Trials.AI utilizes their deep learning tools for efficient clinical trials within protocol development and clinical trial execution, including insight into the patient experience, and observing patient burden with travel times to clinical sites. Likewise, ResMed’s use of AI aims to improve outcomes and patient experience. Through their phone-based patient engagement app, the company has collected over 6 years of sleep data, pertinent for sleep apnea research. In yet another example, the Helix platform highlights the need for more diverse datasets and solutions to target underserved populations. 

From the clinical perspective of Dr. Razzelle Kurzrock, Chief, Division of Hematology & Oncology and Director, Center for Personalized Cancer Therapy at UCSD, the oncology space is moving quickly, with new knowledge potentially affecting patient health and outcomes. An immediate need exists to incorporate a system that allows for new findings, an advancement that could optimize a patient’s course of treatment. Her work involves treating end stage patients, while Helix is focused on using data for prevention. For newly diagnosed populations, in early stage disease, treatment plans may prove most effective. As the industry continues to develop these tools and datasets, it will be important to enhance both the methods by which AI algorithms are trained and the business models that will propel AI into successful adoption.

Our own Casey Laris, CTO at  Reveal Biosciences, shared personal insights drawn from a family member’s cancer misdiagnosis, underscoring the importance and pride of everyday personal investment from the Reveal Bio team. Casey demonstrated how imageDx: NASH provides accurate and reproducible quantitative data from human and rodent liver samples to benefit preclinical research, clinical trials, and as a decision support tool for pathologists.    Reveal is developing a pipeline of decision support tools using imageDx, our AI-based pathology platform, to provide pathologists with an enhanced lens into disease. A need for these tools is timely, as a global shortage of pathologists is happening in real time, while the pathology workload continues to increase. imageDx technology increases the accuracy, reproducibility and scale of pathology data to benefit research, patients, and lower the cost of healthcare.  

The Summit also highlighted engaging discussions around strategic partnerships  and investments in the space. On the Start-Up Focused Partnering panel, our CEO, Claire Weston, shared our experience initiating the investor relationship: being out in front and strategically aligning with collaborators working towards the same goal. 

We extend our thanks to Biocom for organizing another great event, providing a space for thought-provoking conversations and networking. We look forward to next year’s summit!


Mary Nguyen, PhD, Business Development Manager, Reveal Biosciences

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